from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 2.128877 | 0.280239 | NaN | 0.000376 | 0.002129 | brute | -1 | 1 | 0.663 | 0.177379 | 0.003063 | 0.687 | 12.001858 | 12.003647 |
| 4 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.823729 | 0.029471 | NaN | 0.000283 | 0.002824 | brute | -1 | 5 | 0.757 | 0.181691 | 0.008840 | 0.742 | 15.541412 | 15.559797 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.106872 | 0.090814 | NaN | 0.000380 | 0.002107 | brute | 1 | 100 | 0.882 | 0.214225 | 0.000397 | 0.875 | 9.834852 | 9.834869 |
| 8 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.019170 | 0.000171 | NaN | 0.000042 | 0.019170 | brute | 1 | 100 | 1.000 | 0.008875 | 0.000180 | 0.000 | 2.160161 | 2.160606 |
| 10 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.871416 | 0.158655 | NaN | 0.000279 | 0.002871 | brute | -1 | 100 | 0.882 | 0.213490 | 0.000831 | 0.875 | 13.449861 | 13.449963 |
| 11 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.024110 | 0.002122 | NaN | 0.000033 | 0.024110 | brute | -1 | 100 | 1.000 | 0.009144 | 0.000937 | 0.000 | 2.636675 | 2.650490 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.059207 | 0.014497 | NaN | 0.000388 | 0.002059 | brute | 1 | 5 | 0.757 | 0.178978 | 0.000666 | 0.742 | 11.505365 | 11.505445 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 1.199453 | 0.005205 | NaN | 0.000667 | 0.001199 | brute | 1 | 1 | 0.663 | 0.176742 | 0.002242 | 0.687 | 6.786464 | 6.787010 |
| 19 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.807085 | 0.033507 | NaN | 0.000009 | 0.001807 | brute | -1 | 1 | 0.896 | 0.026398 | 0.000226 | 0.967 | 68.455327 | 68.457837 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 2.846872 | 0.101212 | NaN | 0.000006 | 0.002847 | brute | -1 | 5 | 0.922 | 0.027683 | 0.000915 | 0.974 | 102.836865 | 102.892971 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 1.964610 | 0.011847 | NaN | 0.000008 | 0.001965 | brute | 1 | 100 | 0.929 | 0.061925 | 0.001297 | 0.975 | 31.725776 | 31.732731 |
| 28 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 2.757163 | 0.043060 | NaN | 0.000006 | 0.002757 | brute | -1 | 100 | 0.929 | 0.061730 | 0.000367 | 0.975 | 44.664636 | 44.665423 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 1.940457 | 0.004650 | NaN | 0.000008 | 0.001940 | brute | 1 | 5 | 0.922 | 0.027534 | 0.000116 | 0.974 | 70.475325 | 70.475950 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.093611 | 0.007729 | NaN | 0.000015 | 0.001094 | brute | 1 | 1 | 0.896 | 0.026411 | 0.000181 | 0.967 | 41.406813 | 41.407790 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.151 | 0.0 | -1 | 1 | 0.049 | 0.004 | 0.231 | 0.231 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.080 | 0.0 | -1 | 5 | 0.048 | 0.000 | 0.237 | 0.237 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.096 | 0.0 | 1 | 100 | 0.047 | 0.000 | 0.242 | 0.242 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.235 | 0.0 | -1 | 100 | 0.048 | 0.000 | 0.231 | 0.231 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.329 | 0.0 | 1 | 5 | 0.047 | 0.000 | 0.230 | 0.230 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.246 | 0.0 | 1 | 1 | 0.048 | 0.000 | 0.231 | 0.231 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.367 | 0.0 | -1 | 1 | 0.009 | 0.000 | 0.499 | 0.499 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.378 | 0.0 | -1 | 5 | 0.009 | 0.000 | 0.485 | 0.485 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.364 | 0.0 | 1 | 100 | 0.008 | 0.000 | 0.519 | 0.519 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.374 | 0.0 | -1 | 100 | 0.009 | 0.000 | 0.496 | 0.497 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.378 | 0.0 | 1 | 5 | 0.008 | 0.000 | 0.500 | 0.500 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.374 | 0.0 | 1 | 1 | 0.009 | 0.000 | 0.503 | 0.503 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.129 | 0.280 | 0.000 | 0.002 | -1 | 1 | 0.177 | 0.003 | 12.002 | 12.004 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 1 | 0.008 | 0.000 | 2.813 | 2.814 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.824 | 0.029 | 0.000 | 0.003 | -1 | 5 | 0.182 | 0.009 | 15.541 | 15.560 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 5 | 0.008 | 0.000 | 2.787 | 2.788 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.107 | 0.091 | 0.000 | 0.002 | 1 | 100 | 0.214 | 0.000 | 9.835 | 9.835 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 100 | 0.009 | 0.000 | 2.160 | 2.161 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.871 | 0.159 | 0.000 | 0.003 | -1 | 100 | 0.213 | 0.001 | 13.450 | 13.450 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 100 | 0.009 | 0.001 | 2.637 | 2.650 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.059 | 0.014 | 0.000 | 0.002 | 1 | 5 | 0.179 | 0.001 | 11.505 | 11.505 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.001 | 0.000 | 0.020 | 1 | 5 | 0.009 | 0.000 | 2.286 | 2.286 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.199 | 0.005 | 0.001 | 0.001 | 1 | 1 | 0.177 | 0.002 | 6.786 | 6.787 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 1 | 0.009 | 0.000 | 2.077 | 2.077 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.807 | 0.034 | 0.000 | 0.002 | -1 | 1 | 0.026 | 0.000 | 68.455 | 68.458 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.004 | 0.000 | 0.006 | -1 | 1 | 0.001 | 0.000 | 8.890 | 8.976 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.847 | 0.101 | 0.000 | 0.003 | -1 | 5 | 0.028 | 0.001 | 102.837 | 102.893 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.002 | 0.000 | 0.007 | -1 | 5 | 0.001 | 0.000 | 9.744 | 9.822 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.965 | 0.012 | 0.000 | 0.002 | 1 | 100 | 0.062 | 0.001 | 31.726 | 31.733 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 4.029 | 4.076 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.757 | 0.043 | 0.000 | 0.003 | -1 | 100 | 0.062 | 0.000 | 44.665 | 44.665 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.003 | 0.000 | 0.006 | -1 | 100 | 0.001 | 0.000 | 8.042 | 8.148 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.940 | 0.005 | 0.000 | 0.002 | 1 | 5 | 0.028 | 0.000 | 70.475 | 70.476 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 4.439 | 4.490 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.094 | 0.008 | 0.000 | 0.001 | 1 | 1 | 0.026 | 0.000 | 41.407 | 41.408 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.680 | 2.697 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.822431 | 0.945738 | NaN | 0.000097 | 0.000822 | kd_tree | -1 | 1 | 0.929 | 0.118045 | 0.001756 | 0.910 | 6.967104 | 6.967875 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 0.982356 | 0.301064 | NaN | 0.000081 | 0.000982 | kd_tree | -1 | 5 | 0.946 | 0.207160 | 0.001510 | 0.941 | 4.742026 | 4.742152 |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 5.425400 | 0.346854 | NaN | 0.000015 | 0.005425 | kd_tree | 1 | 100 | 0.951 | 0.628470 | 0.007008 | 0.940 | 8.632716 | 8.633253 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 3.143240 | 0.243197 | NaN | 0.000025 | 0.003143 | kd_tree | -1 | 100 | 0.951 | 0.608801 | 0.016553 | 0.940 | 5.163001 | 5.164910 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.580989 | 0.122073 | NaN | 0.000051 | 0.001581 | kd_tree | 1 | 5 | 0.946 | 0.208965 | 0.002489 | 0.941 | 7.565825 | 7.566362 |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.873094 | 0.101119 | NaN | 0.000092 | 0.000873 | kd_tree | 1 | 1 | 0.929 | 0.112327 | 0.000928 | 0.910 | 7.772759 | 7.773024 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.026312 | 0.012533 | NaN | 0.000608 | 0.000026 | kd_tree | -1 | 1 | 0.891 | 0.000397 | 0.000043 | 0.879 | 66.273894 | 66.662519 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.022179 | 0.000887 | NaN | 0.000721 | 0.000022 | kd_tree | -1 | 5 | 0.911 | 0.000640 | 0.000031 | 0.905 | 34.666595 | 34.707293 |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.034549 | 0.005975 | NaN | 0.000463 | 0.000035 | kd_tree | 1 | 100 | 0.894 | 0.004486 | 0.000021 | 0.917 | 7.700813 | 7.700901 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.036180 | 0.003305 | NaN | 0.000442 | 0.000036 | kd_tree | -1 | 100 | 0.894 | 0.005276 | 0.001011 | 0.917 | 6.857128 | 6.981983 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.020111 | 0.000106 | NaN | 0.000796 | 0.000020 | kd_tree | 1 | 5 | 0.911 | 0.000642 | 0.000022 | 0.905 | 31.341430 | 31.360172 |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.018866 | 0.000149 | NaN | 0.000848 | 0.000019 | kd_tree | 1 | 1 | 0.891 | 0.000381 | 0.000027 | 0.879 | 49.485903 | 49.610924 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.332 | 0.068 | 0.024 | 0.0 | -1 | 1 | 0.776 | 0.088 | 4.294 | 4.322 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.659 | 0.054 | 0.022 | 0.0 | -1 | 5 | 0.734 | 0.012 | 4.988 | 4.988 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.496 | 0.084 | 0.023 | 0.0 | 1 | 100 | 0.729 | 0.006 | 4.792 | 4.792 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.618 | 0.073 | 0.022 | 0.0 | -1 | 100 | 0.727 | 0.009 | 4.976 | 4.977 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.372 | 0.061 | 0.024 | 0.0 | 1 | 5 | 0.726 | 0.005 | 4.643 | 4.643 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.487 | 0.058 | 0.023 | 0.0 | 1 | 1 | 0.731 | 0.008 | 4.770 | 4.771 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.021 | 0.0 | -1 | 1 | 0.003 | 0.001 | 0.287 | 0.321 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.028 | 0.0 | -1 | 5 | 0.001 | 0.001 | 0.489 | 0.638 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.512 | 0.588 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.630 | 0.635 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.640 | 0.642 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.672 | 0.672 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.822 | 0.946 | 0.000 | 0.001 | -1 | 1 | 0.118 | 0.002 | 6.967 | 6.968 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.002 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 12.339 | 13.178 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.982 | 0.301 | 0.000 | 0.001 | -1 | 5 | 0.207 | 0.002 | 4.742 | 4.742 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.000 | 0.000 | 7.947 | 8.428 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.425 | 0.347 | 0.000 | 0.005 | 1 | 100 | 0.628 | 0.007 | 8.633 | 8.633 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 4.187 | 4.432 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.143 | 0.243 | 0.000 | 0.003 | -1 | 100 | 0.609 | 0.017 | 5.163 | 5.165 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 0.001 | 0.000 | 6.522 | 6.888 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.581 | 0.122 | 0.000 | 0.002 | 1 | 5 | 0.209 | 0.002 | 7.566 | 7.566 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.001 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 3.708 | 3.988 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.873 | 0.101 | 0.000 | 0.001 | 1 | 1 | 0.112 | 0.001 | 7.773 | 7.773 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 3.913 | 4.193 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.013 | 0.001 | 0.000 | -1 | 1 | 0.000 | 0.000 | 66.274 | 66.663 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 27.669 | 28.931 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 34.667 | 34.707 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 22.378 | 23.158 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.006 | 0.000 | 0.000 | 1 | 100 | 0.004 | 0.000 | 7.701 | 7.701 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 5.491 | 5.648 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.036 | 0.003 | 0.000 | 0.000 | -1 | 100 | 0.005 | 0.001 | 6.857 | 6.982 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 21.617 | 22.365 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.020 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 31.341 | 31.360 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 6.394 | 6.614 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.000 | 0.000 | 49.486 | 49.611 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 6.764 | 7.022 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.507 | 0.059 | 30 | 0.032 | 0.0 | random | 0.377 | 0.022 | 1.344 | 1.347 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.556 | 0.011 | 30 | 0.029 | 0.0 | k-means++ | 0.406 | 0.025 | 1.368 | 1.370 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.512 | 0.158 | 30 | 0.145 | 0.0 | random | 2.660 | 0.069 | 2.072 | 2.073 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.714 | 0.041 | 30 | 0.140 | 0.0 | k-means++ | 2.805 | 0.022 | 2.037 | 2.037 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.001 | 0.000 | 30 | 0.011 | 0.000 | random | 0.0 | 0.0 | 8.256 | 12.761 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | random | 0.0 | 0.0 | 9.416 | 14.262 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.001 | 0.000 | 30 | 0.011 | 0.000 | k-means++ | 0.0 | 0.0 | 10.594 | 12.247 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | k-means++ | 0.0 | 0.0 | 12.974 | 13.691 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.001 | 30 | 0.438 | 0.000 | random | 0.0 | 0.0 | 7.317 | 7.984 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | random | 0.0 | 0.0 | 11.723 | 12.025 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.482 | 0.000 | k-means++ | 0.0 | 0.0 | 6.590 | 7.124 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | k-means++ | 0.0 | 0.0 | 13.242 | 13.774 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 0.001090 | 10000 | 1000 | 2 | 0.001783 | 0.000186 | 20 | 0.008972 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000126 | 0.000418 | 0.000025 | -0.000965 | 4.262749 | 4.270442 |
| 4 | KMeans_short | predict | 0.001995 | 10000 | 1000 | 2 | 0.001755 | 0.000134 | 20 | 0.009115 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.001245 | 0.000443 | 0.000046 | -0.000750 | 3.962905 | 3.983765 |
| 7 | KMeans_short | predict | 0.015034 | 10000 | 1000 | 100 | 0.002475 | 0.000265 | 20 | 0.323267 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.278733 | 0.000928 | 0.000073 | 0.293767 | 2.667425 | 2.675672 |
| 10 | KMeans_short | predict | 0.060044 | 10000 | 1000 | 100 | 0.002381 | 0.000160 | 20 | 0.336029 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.317011 | 0.000938 | 0.000090 | 0.256968 | 2.537614 | 2.549158 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.072 | 0.000 | 20 | 0.002 | 0.0 | random | 0.026 | 0.002 | 2.772 | 2.780 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.207 | 0.001 | 20 | 0.001 | 0.0 | k-means++ | 0.082 | 0.000 | 2.512 | 2.512 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.189 | 0.001 | 20 | 0.042 | 0.0 | random | 0.105 | 0.001 | 1.795 | 1.795 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.556 | 0.007 | 20 | 0.014 | 0.0 | k-means++ | 0.304 | 0.000 | 1.825 | 1.825 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | random | 0.000 | 0.0 | 4.263 | 4.270 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | random | 0.000 | 0.0 | 13.349 | 13.660 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | k-means++ | 0.000 | 0.0 | 3.963 | 3.984 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | k-means++ | 0.000 | 0.0 | 12.980 | 13.433 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.323 | 0.000 | random | 0.001 | 0.0 | 2.667 | 2.676 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | random | 0.000 | 0.0 | 10.706 | 10.912 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.336 | 0.000 | k-means++ | 0.001 | 0.0 | 2.538 | 2.549 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | k-means++ | 0.000 | 0.0 | 10.382 | 10.601 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 0.01 | 1000000 | 1000 | 100 | 0.000359 | 0.000357 | [20] | 2.226769 | 3.592650e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.56 | 0.000601 | 0.000925 | 0.55 | 0.597755 | 1.097477 |
| 4 | LogisticRegression | predict | 0.07 | 1000 | 100 | 10000 | 0.001579 | 0.000373 | [26] | 5.067293 | 1.578752e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.35 | 0.005017 | 0.000851 | 0.28 | 0.314701 | 0.319197 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 11.123 | 0.416 | [20] | 0.072 | 0.000 | 1.915 | 0.013 | 5.807 | 5.807 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 0.889 | 0.401 | [26] | 0.090 | 0.001 | 0.844 | 0.031 | 1.053 | 1.054 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 2.227 | 0.0 | 0.001 | 0.001 | 0.598 | 1.097 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.015 | 0.0 | 0.000 | 0.000 | 0.402 | 0.408 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 5.067 | 0.0 | 0.005 | 0.001 | 0.315 | 0.319 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 1.087 | 0.0 | 0.001 | 0.000 | 0.049 | 0.049 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | diff_r2_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 0.039624 | 1000 | 1000 | 10000 | 0.011297 | 0.000278 | NaN | 7.081458 | 0.000011 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.082567 | 0.018065 | 0.000127 | 0.122191 | 0.625343 | 0.625359 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.170 | 0.002 | 0.470 | 0.0 | 0.178 | 0.000 | 0.957 | 0.957 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.085 | 0.052 | 0.738 | 0.0 | 0.314 | 0.286 | 3.451 | 4.666 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.011 | 0.0 | 7.081 | 0.0 | 0.018 | 0.0 | 0.625 | 0.625 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | 1.361 | 0.0 | 0.000 | 0.0 | 0.594 | 0.643 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | 5.637 | 0.0 | 0.000 | 0.0 | 0.425 | 0.666 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | 0.017 | 0.0 | 0.000 | 0.0 | 0.600 | 0.633 | See | See |